ZipRecruiter

Log In

2

Remote Large Language Model Llm Jobs in California

Twenty80 LLC

AI Engineer

San Mateo, CA · Remote

Hands-on experience with large language model (LLM) inference and/or model training using open ... Remote-friendly within the United States * Preference for candidates located near major East or ...

Redfish Recruiting

... large language model (LLM) capabilities, and AI infrastructure. Own how models, evaluation ... Fully remote, work from home environment * Employee Share Option Plan * Flexible working hours

PA Early Stage Partners

Senior Software Engineer

Sunnyvale, CA · On-site +1

$143K - $189K/yr

Backend Integration of LLM Architectures : Lead the development and maintenance of the backend infrastructure that powers state-of-the-art Large Language Model (LLM) architectures, including RAG ...

Aquent

Software Engineer

Folsom, CA · On-site +1

$75.50 - $102/hr

Hands-on experience integrating with large language model (LLM) APIs, such as those from leading providers or similar platforms. * Familiarity with CI/CD platforms and best practices. * A strong ...

next page

Showing results 1-20

All JobsLarge Language Model Llm JobsRemote Large Language Model Llm JobsRemote Large Language Model Llm Jobs in California

Remote Large Language Model Llm information

What is a remote large language model LLM?

A Remote Large Language Model (LLM) job involves working with advanced AI models, like GPT or similar, from a remote location. Professionals in these roles may develop, train, fine-tune, or implement large language models for various applications such as natural language processing, chatbots, or content generation. Remote LLM jobs can include positions like machine learning engineer, research scientist, or AI product manager. The work typically requires strong programming skills, experience with AI frameworks, and the ability to collaborate virtually with global teams.

How does a remote large language model LLM engineer typically collaborate with cross-functional teams while working remotely?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers through virtual meetings, collaborative coding platforms, and shared documentation tools. Regular communication is key, with daily stand-ups or weekly syncs to align on project goals, update progress, and address challenges. They may also participate in code reviews, contribute to design discussions, and support model deployment efforts, all within a distributed team environment. This remote structure encourages self-motivation and proactive communication to ensure project success.

What are the key skills and qualifications needed to thrive as a remote large language model LLM engineer?

To thrive as a Remote Large Language Model (LLM) Engineer, you need a strong background in computer science, machine learning, and natural language processing, typically supported by a relevant degree and experience with large-scale models. Proficiency with programming languages like Python, deep learning frameworks such as PyTorch or TensorFlow, and familiarity with cloud platforms and distributed systems are essential. Excellent problem-solving, communication, and collaboration skills are critical for remote teamwork and translating complex requirements into scalable solutions. These skills ensure the effective development, deployment, and maintenance of advanced language models in fast-evolving, distributed environments.

What is the difference between Remote Large Language Model Llm vs Data Scientist?

AspectRemote Large Language Model LlmData Scientist
Required CredentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learning frameworksDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentPrimarily remote, focused on developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and generating insights
Employer & Industry UsageTech companies, AI research labs, startups working on NLP productsTech firms, finance, healthcare, marketing, and research organizations

While both roles involve data and machine learning, a Remote Large Language Model Llm specializes in developing and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various domains.

What are the most commonly searched types of Large Language Model Llm jobs in California? The most popular types of Large Language Model Llm jobs in California are:
What are popular job titles related to Remote Large Language Model Llm jobs in California? For Remote Large Language Model Llm jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Large Language Model Llm jobs in California look for? The top searched job categories for Remote Large Language Model Llm jobs in California are:
What cities in California are hiring for Remote Large Language Model Llm jobs? Cities in California with the most Remote Large Language Model Llm job openings:
Remote Large Language Model Llm jobs near you
Infographic showing various Remote Large Language Model Llm job openings in California as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

AI Engineer

Twenty80 LLC

San Mateo, CA • Remote

Full-time

Medical, Dental, Vision

Posted 9 days ago

Job description

Role Summary

Our client, a rapidly growing AI infrastructure company, is seeking multiple AI Engineers (Enterprise) to help design, build, and deploy production-grade generative AI solutions for enterprise customers.

This is a customer-facing, hands-on engineering role that combines deep technical expertise with solution architecture and client engagement. You will partner closely with enterprise organizations to transform generative AI concepts into scalable production systems while collaborating with internal engineering and product teams to drive innovation.

Strong candidates will have experience deploying AI/ML solutions in production environments, working with large language models (LLMs), and supporting enterprise customers through complex technical implementations.

Key ResponsibilitiesEnterprise AI Solutions
  • Lead technical discovery sessions with enterprise customers to understand business requirements and define AI solution strategies.
  • Scope and execute proof-of-concept (POC) projects, performance testing, and solution evaluations.
  • Design, build, and deploy production-ready AI applications within customer environments.
  • Recommend appropriate model architectures, deployment strategies, and infrastructure based on customer requirements.
  • Advise customers on model fine-tuning and optimization techniques, including supervised fine-tuning and other modern training approaches.
  • Develop evaluation frameworks to measure model performance and production readiness.
Customer Engagement
  • Serve as the primary technical advisor for enterprise customers throughout implementation and deployment.
  • Build relationships with technical and executive stakeholders.
  • Guide customers through infrastructure, security, and compliance considerations.
  • Support successful production rollouts and ongoing technical adoption.
Cross-Functional Collaboration
  • Partner with Product and Engineering teams to communicate customer feedback and influence product improvements.
  • Identify recurring customer challenges and contribute to product roadmap discussions.
  • Collaborate internally to improve deployment processes and customer success.
Required Qualifications
  • 3+ years of experience in customer-facing AI/ML, machine learning infrastructure, solutions engineering, or related technical roles
  • Proven experience deploying AI/ML applications into production environments
  • Hands-on experience with large language model (LLM) inference and/or model training using open-source model frameworks
  • Strong Python programming skills
  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
  • Experience with containerization and orchestration technologies, including Kubernetes
  • Excellent communication skills with the ability to engage both technical teams and executive stakeholders
  • Ability to manage multiple enterprise projects in a fast-paced environment
Preferred Qualifications
  • Experience with modern LLM fine-tuning methodologies such as supervised fine-tuning (SFT) and other advanced optimization techniques
  • Background in enterprise AI solution architecture or technical consulting
  • Experience working within high-growth startup environments
  • Strong understanding of enterprise infrastructure, security, and compliance requirements
  • Experience supporting large-scale customer deployments
Ideal Candidate Profile

Successful candidates typically have:

  • Experience building and deploying production AI solutions rather than purely research or advisory work
  • Strong knowledge of open-source LLM frameworks and inference platforms
  • Experience working directly with enterprise customers throughout implementation and deployment
  • The ability to translate complex technical concepts for both engineering teams and executive leadership
  • A collaborative mindset with a passion for solving complex customer challenges
  • Experience working in fast-paced, high-growth environments
Schedule & Travel
  • Full-time position
  • Remote-friendly within the United States
  • Preference for candidates located near major East or West Coast metropolitan areas, though exceptional remote candidates will be considered
  • Regular domestic travel to customer sites for technical discovery, proof-of-concept implementations, and production deployments
Compensation
  • Competitive base salary
  • Performance-based bonus or on-target earnings (OTE)
  • Equity package
  • Compensation commensurate with experience and qualifications
Benefits
  • Comprehensive medical, dental, and vision insurance
  • Equity participation
  • Performance-based bonus opportunities
  • Flexible remote work environment
  • Professional development and career growth opportunities
  • Opportunity to work with cutting-edge generative AI technologies on enterprise-scale deployments
  • Collaborative, fast-paced engineering culture